Spatial processing with antenna arrays is one of the most used techniques in wireless communications. Among many schemes developed to date, multiple-input multiple-output (MIMO) and beamforming are often studied and have been proved to be effective in increasing the capacity and performance of a wireless network (see, e.g., Ayman F. Naguib, Vahid Tarokh, Nambirajan Seshadri, A. Robert Calderbank, “A Space-Time Coding Modem for High-Data-Rate Wireless Communications”, IEEE Journal on Selected Areas in Communications, vol. 16, no. 8, October 1998 pp. 1459-1478). On the other hand, realization of MIMO or beamforming often means higher complexity and cost on the system side. In particular, MIMO operations entail complicated signal processing and decoding, while beamforming involves hardware calibrations and multi-dimensional data processing.
Over the years, orthogonal division multiple-access (OFDMA) has become the access scheme of choice for almost all broadband wireless networks (e.g., WiMAX, WiFi, and 4G cellular systems). In OFDMA, multiple subscribers are allocated to different subcarriers, in a fashion similar to frequency division multiple access (FDMA). For more information, see Sari and Karam, “Orthogonal Frequency-Division Multiple Access and its Application to CATV Networks,” European Transactions on Telecommunications, Vol. 9 (6), pp. 507-516, November/December 1998 and Nogueroles, Bossert, Donder, and Zyablov, “Improved Performance of a Random OFDMA Mobile Communication System,” Proceedings of IEEE VTC '98, pp. 2502-2506.
The fundamental phenomenon that makes reliable wireless transmission difficult to achieve is time-varying multipath fading. Increasing the quality or reducing the effective error rate in a multipath fading channel may be extremely difficult. For instance, consider the following comparison between a typical noise source in a non-multipath environment and multipath fading. In environments having additive white Gaussian noise (AWGN), it may require only 1- or 2-db higher signal-to-noise ratio (SNR) using typical modulation and coding schemes to reduce the effective bit error rate (BER) from 10−2 to 10−3. Achieving the same reduction in a multipath fading environment, however, may require up to 10 db improvement in SNR. The necessary improvement in SRN may not be achieved by simply providing higher transmit power or additional bandwidth, as this is contrary to the requirements of next generation broadband wireless systems.
Multipath phenomena causes frequency-selective fading. In a multiuser fading environment, the channel gains are different for different subcarriers. Furthermore, the channels are typically uncorrelated for different subscribers. This leads to a so-called “multiuser diversity” gain that can be exploited through intelligent subcarrier allocation. In other words, it is advantageous in an OFDMA system to adaptively allocate the subcarriers to subscribers so that each subscriber enjoys a high channel gain. For more information, see Wong et al., “Multiuser OFDM with Adaptive Subcarrier, Bit and Power Allocation,” IEEE J. Select. Areas Commun., Vol. 17(10), pp. 1747-1758, October 1999.
Within one cell, the subscribers can be coordinated to have different subcarriers in OFDMA. The signals for different subscribers can be made orthogonal and there is little intracell interference. However, with an aggressive frequency reuse plan, e.g., the same spectrum is used for multiple neighboring cells, the problem of intercell interference arises. It is clear that the intercell interference in an OFDMA system is also frequency selective and it is advantageous to adaptively allocate the subcarriers so as to mitigate the effect of intercell interference.
One approach to subcarrier allocation for OFDMA is a joint optimization operation, not only requiring the activity and channel knowledge of all the subscribers in all the cells, but also requiring frequent rescheduling every time an existing subscribers is dropped off the network or a new subscribers is added onto the network. This is often impractical in real wireless system, mainly due to the bandwidth cost for updating the subscriber information and the computation cost for the joint optimization.
Existing approaches for wireless traffic channel assignment are subscriber-initiated and single-subscriber (point-to-point) in nature. Since the total throughput of a multiple-access network depends on the channel fading profiles, noise-plus-interference levels, and in the case of spatially separately transceivers, the spatial channel characteristics, of all active subscribers, distributed or subscriber-based channel loading approaches are fundamentally sub-optimum. Furthermore, subscriber-initiated loading algorithms are problematic when multiple transceivers are employed as the base-station, since the signal-to-noise-plus-interference ratio (SINR) measured based on an omni-directional sounding signal does not reveal the actual quality of a particular traffic channel with spatial processing gain. In other words, a “bad” traffic channel measured at the subscriber based on the omni-directional sounding signal may very well be a “good” channel with proper spatial beamforming from the base-station. For these two reasons, innovative information exchange mechanisms and channel assignment and loading protocols that account for the (spatial) channel conditions of all accessing subscribers, as well as their QoS requirements, are highly desirable. Such “spatial-channel and QoS-aware” allocation schemes can considerably increase the spectral efficiency and hence data throughput in a given bandwidth. Thus, distributed approaches, i.e., subscriber-initiated assignment are fundamentally sub-optimum.